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IJCAI
2003
14 years 3 days ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
PR
2007
148views more  PR 2007»
13 years 10 months ago
Learning the best subset of local features for face recognition
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
Berk Gökberk, M. Okan Irfanoglu, Lale Akarun,...
CVPR
2008
IEEE
15 years 23 days ago
Discriminative learned dictionaries for local image analysis
Sparse signal models have been the focus of much recent research, leading to (or improving upon) state-of-the-art results in signal, image, and video restoration. This article ext...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
ICPR
2002
IEEE
14 years 11 months ago
Unsupervised Learning Using Locally Linear Embedding: Experiments with Face Pose Analysis
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
Abdenour Hadid, Matti Pietikäinen, Olga Kouro...
ICPR
2008
IEEE
14 years 5 months ago
An improvement on learning with local and global consistency
A modified version for semi-supervised learning algorithm with local and global consistency was proposed in this paper. The new method adds the label information, and adopts the g...
Jie Gui, De-Shuang Huang, Zhuhong You